{"id":"W3046047898","doi":"10.1109/icc40277.2020.9148735","title":"A Novel Joint Data Gathering and Wireless Charging Scheme for Sustainable Wireless Sensor Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Wireless sensor network; Energy consumption; Wireless; Computer network; Scheduling (production processes); Key distribution in wireless sensor networks; Cluster analysis; Data collection; Efficient energy use; Inductive charging; Wireless network; Latency (audio); Real-time computing; Engineering; Telecommunications; Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000401875,0.0005257995,0.0005905621,0.0004744509,0.0007283647,0.0005228606,0.001218867,0.0004103632,0.001193709],"category_scores_gemma":[0.000764712,0.0001853812,0.0003818595,0.0009329013,0.0002906457,0.001009433,0.0007578849,0.0004383453,0.0002785693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005490507,"about_ca_system_score_gemma":0.0008095074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00112149,"about_ca_topic_score_gemma":0.001628871,"domain_scores_codex":[0.9996082,0.00007857905,0.0000288347,0.00008102086,0.0001394284,0.00006389028],"domain_scores_gemma":[0.9997174,0.00005624498,0.00003293741,0.00005701994,0.0001018548,0.00003447295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005955065,0.0002677187,0.001627932,0.0004395944,0.0001120955,0.0005028855,0.0003902311,0.3023695,0.1147352,0.07520261,0.009433838,0.4943229],"study_design_scores_gemma":[0.00003579528,0.0002708194,0.0003301277,0.00001293296,0.00002890423,0.0003629175,0.00006580741,0.966732,0.01371151,0.009243659,0.009170024,0.0000354365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02375183,0.0006359683,0.9706497,0.0002205926,0.0001777456,0.000103761,0.00005000523,0.0004351361,0.003975244],"genre_scores_gemma":[0.8599243,0.0005911968,0.1346291,0.0001570924,0.00009530874,0.0001390756,0.0001010598,0.00004300069,0.004319787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001218867,"threshold_uncertainty_score":0.003993332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04163786506998973,"score_gpt":0.2266795641889303,"score_spread":0.1850416991189406,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}